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Title page for ETD etd-07232008-170634
|Type of Document
||Improved imaging of brain white matter using diffusion weighted magnetic resonance imaging
|Adam W. Anderson, Ph. D.
|Bruce M. Damon, Ph. D.
|John C. Gore, Ph. D.
|Mark D. Does, Ph. D.
|Zhaohua Ding, Ph. D.
- ultra high magnetic field
- high angular resolution diffusion imaging
- diffusion tensor magnetic resonance imaging
- brain white matter
- cone of uncertainty
- spherical deconvolution
- field inhomogeneity correction
- Brain -- Magnetic resonance imaging
- Diffusion magnetic resonance imaging
- Diffusion tensor imaging
|Date of Defense
Diffusion weighted magnetic resonance imaging (DW-MRI) is an imaging technique that provides a measure of local tissue microstructure based on the water molecular diffusion. Although this imaging method has been successfully used in investigating brain white matter for normal and various dysfunctional states, major limitations of this technique have recently been identified. In diffusion tensor MRI (DT-MRI), image noise produces both noise and bias in the estimated tensor, and leads to errors in estimated axonal fiber pathways. Moreover the single-tensor model is inappropriate in regions with non-parallel fiber structure.
Several high angular resolution diffusion imaging (HARDI) methods have been proposed as alternative tools for resolving multiple fiber structures within a single voxel. At low SNR, however, fiber orientation from HARDI becomes unreliable. Also none of the HARDI methods can provide estimates of the intrinsic diffusion properties of any of the fibers. Addressing limitations of this technique, we suggest improved imaging methods for brain white matter in conventional and ultra high field imaging environments.
This study provides experimental and theoretical results about the uncertainty in fiber orientation using DT-MRI. It proposes methods for the estimation of intrinsic diffusion properties as well as reliable fiber orientation distribution (FOD) functions using HARDI with simulations and in vivo experiments. These methods are then applied to ultra high field strength experiments using a field inhomogeneity correction for image distortions. In summary, the results of this study provide improved diffusion imaging methods for human and/or non-human primates.
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